Optimizing key-value stores for hybrid storage architectures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Flash-based solid state drives (SSDs) are increas-ingly becoming a popular choice as a storage de-vice within database management systems and key-value stores alike. SSDs offer fast throughput and low latency access to data, but their price-per-byte cost often makes them uneconomical for exclusive use, especially in the era of big data workloads. A common solution to this problem is to augment existing database systems by adding smaller SSDs that target only performance-critical areas. We be-lieve this hybrid approach to be a stop-gap solution. Rather than simply extending existing systems with SSDs, in this work we completely re-architect how a key-value database operates in a hybrid stor-age setting with both small but fast SSDs and slower but high-capacity HDDs. We formulate an accurate I/O cost model to study how popular key-value stores behave under several varying represen-tative workloads. Based on these studies and tak-ing a holistic approach, we design a system that dynamically optimizes the data layout and access strategy that leverages the strengths of each avail-able storage medium. 1
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it